Modular AI Agent Design with LangChain and MCP: A Developer’s Guide to Building Scalable, Graph-Based Intelligent Systems with Design Patterns - Tapa blanda

Modular AI Agent Design with LangChain and MCP (Paperback)

Paperback. Condición: new. Paperback. Modular AI Agent Design with LangChain and MCP: A Developer's Guide to Building Scalable, Graph-Based Intelligent Systems with Design Patterns Unlock the future of intelligent systems with modular AI agents scalable, adaptable, and built to last. As artificial intelligence systems grow in complexity, developers need frameworks that ensure flexibility, scalability, and maintainability. Modular AI Agent Design with LangChain and MCP is a hands-on guide to building next-generation AI agents using the power of LangChain, the Model Context Protocol (MCP), and proven software design patterns.This book bridges theory and practice by walking you through modular architectures, agent communication protocols, graph-based workflows, and real-world deployment strategies. Each chapter provides practical examples, well-documented code snippets, and step-by-step explanations to help you design AI systems that can evolve with emerging technologies.Whether you are building single-purpose agents or multi-agent ecosystems, this guide equips you with the tools to create robust, production-ready systems that are both technically sound and future-proof.Key Features: Learn how to design modular AI agents using LangChain and MCP.Apply classic design patterns (Factory, Strategy, Observer, Composite) to AI workflows.Build scalable multi-agent systems with graph-based architectures.Master deployment strategies across cloud, edge, and hybrid environments.Access reference code snippets and resources for rapid prototyping.If you're ready to design AI agents that scale with complexity and stand the test of time, add Modular AI Agent Design with LangChain and MCP to your library today. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798264542664

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